Heavybit Podcasts

On episode 33 of Open Source Ready, Brian Douglas and John McBride sit down with James Strong and Marco Ebert. They discuss the retirement of Ingress NGINX, one of the most widely used Kubernetes ingress controllers, and the factors that led to its deprecation. The conversation explores maintainer burnout, major security vulnerabilities like IngressNightmare, and the ecosystem’s shift toward Gateway API.

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In this debut episode of Third Loop, James Governor, Kim Harrison, Heidi Waterhouse, and Adam Zimman explore how the concept of Progressive Delivery emerged from real-world frustrations with how the industry talked about shipping software. Drawing on experiences from companies like GitHub and LaunchDarkly, they explain how practices like feature flags, experimentation, and observability came together to form a new delivery model. The conversation also sets the stage for the podcast’s broader mission: examining technology through the perspectives of builders, users, and observers.

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On episode 7 of High Leverage, Joe Ruscio sits down with Peter Bell to explore how the CTO role evolves from early-stage founder to enterprise leader. They unpack what it really takes to scale AI adoption across an engineering organization, and why simply buying tools isn’t enough. The conversation dives into agentic software development, observability, context engineering, and what happens when production code is generated without direct human review.

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On episode 49 of The Kubelist Podcast, Marc Campbell and Benjie De Groot sit down with Felipe Huici to explore how unikernels are reshaping modern cloud infrastructure. They discuss virtualization, containers, and how Unikraft enables millisecond startup times and massive workload density. The conversation dives deep into performance engineering, Kubernetes integration, and the infrastructure challenges emerging in the AI era.

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On episode 9 of Data Renegades, CL Kao and Dori Wilson sit down with Wes McKinney, creator of Pandas and co-creator of Apache Arrow. They explore how AI coding agents are reshaping software development, why data infrastructure remains surprisingly resistant to automation, and what semantic layers mean for the future of analytics. Wes also shares bold predictions about “radical accountability” in software and the changing bar for startups.

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On episode 32 of Open Source Ready, Brian Douglas and John McBride sit down with Glauber Costa to explore Turso, a Rust-based rewrite of SQLite built for the AI era. They discuss database reliability, open source licensing, and why embedded databases are becoming critical infrastructure for modern agents and applications. The conversation also dives into AI-assisted development and the future of software engineering.

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On episode 52 of Generationship, Rachel Chalmers sits down with Piyush Agarwal to explore how developer behavior reveals far more about buying intent than traditional sales signals. They discuss why most dev tool GTM strategies fail, how to distinguish curiosity from real demand, and what it takes to engage developers at exactly the right moment.

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On episode 8 of Data Renegades, CL Kao and Dori Wilson sit down with Scott Breitenother to explore how AI is reshaping the modern data stack and redefining the role of data teams. They discuss the evolution from spreadsheets to autonomous agents, the realities of data democratization, and why future workflows may revolve around one human working alongside multiple AI assistants. The conversation blends practical lessons from building Brooklyn Data and Kilo Code with forward-looking predictions about the next wave of data tooling.

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In episode 31 of Open Source Ready, Brian and John sit down with Matthaus Krzykowski, Thierry Jean, and Elvis Kahoro to explore how dlt and dltHub are changing the way developers build data pipelines. The conversation dives into DuckDB, LLM-driven workflows, and the growing shift toward developer-first data engineering. They also discuss open source adoption, AI orchestration, and what it means to be a “10x engineer” in 2026.

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On episode 7 of Data Renegades, CL Kao and Dori Wilson sit down with Bryan Bischof to explore his journey from pure mathematics to building real-world ML systems. They dig into recommender systems, surprising data bugs, and why truth-seeking should guide data teams. The conversation also covers modern data tools, visualization limits, and the realities of “self-serve” analytics.

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